亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Towards 360 VR Sickness Mitigation: From Virtual Reality Eye-tracking to Visual Communication

虚拟现实 计算机科学 模拟病 眼动 可视化 人机交互 数据可视化 多媒体 计算机视觉 视觉传达 计算机图形学(图像) 人工智能
作者
Jeonghaeng Lee,Woojae Kim,Chao Yang,Ping An,Sanghoon Lee
出处
期刊:IEEE Transactions on Visualization and Computer Graphics [Institute of Electrical and Electronics Engineers]
卷期号:: 1-13
标识
DOI:10.1109/tvcg.2024.3447838
摘要

Most 360 virtual reality (VR) contents have been developed without considering that users could be affected by VR sickness. Accordingly, users' viewing safety has been steadily highlighted as a critical problem in the VR market. In this study, we investigate a novel VR sickness mitigation framework based on human visual characteristics for the rendered VR content. First, we build a large-scale 360 VR content database termed VRSP360 (VR Sickness and Presence 360) dedicated to the analysis of VR sickness and thoroughly conduct eye-tracking experiments to measure human perception. In the experiment, we observe that the users' gaze distribution is highly center-biased when they experience excessive VR sickness. From this observation, we design a foveated filtering framework that limits high-frequency textures in the peripheral view to mitigate VR sickness. Particularly, given the human visual system's (HVS) non-uniform resolution with respect to the fovea, we also adopt the foveation-based filtering method using the trade-off between sickness mitigation and presence conservation, which reduces any loss in perceptual quality despite the filtering. We further demonstrate that our framework can effectively compress visual information by applying foveated compression. In addition, we develop two metrics (visual texture index and perceptual information index) to measure the effective preservation of user-perceived information despite the filtration of peripheral vision textures by our proposed mitigation method. Through rigorous subjective evaluation on both original content and its VR-sickness-mitigated version, we demonstrate that the proposed framework successfully mitigates VR sickness with a reduction rate of ∼ 19% on the proposed dataset.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小巧如音完成签到,获得积分10
7秒前
clhoxvpze完成签到 ,获得积分10
10秒前
满意若灵完成签到,获得积分20
11秒前
13秒前
满意若灵发布了新的文献求助10
16秒前
Revision完成签到,获得积分10
31秒前
张利奥完成签到,获得积分10
34秒前
38秒前
flora完成签到 ,获得积分10
41秒前
科研通AI6.3应助shareef采纳,获得10
42秒前
h0jian09完成签到,获得积分10
43秒前
44秒前
张利奥发布了新的文献求助10
45秒前
linvs发布了新的文献求助10
51秒前
56秒前
56秒前
1分钟前
泥豪泥嚎完成签到,获得积分10
1分钟前
852应助h0jian09采纳,获得10
1分钟前
正直的晋鹏完成签到,获得积分10
1分钟前
魔女完成签到,获得积分10
1分钟前
1分钟前
1分钟前
h0jian09发布了新的文献求助10
1分钟前
cbro发布了新的文献求助10
1分钟前
香蕉觅云应助369ninja采纳,获得10
1分钟前
shuiyu完成签到,获得积分10
1分钟前
1分钟前
慕青应助科研通管家采纳,获得10
1分钟前
1分钟前
沐木完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
369ninja发布了新的文献求助10
1分钟前
单纯水桃完成签到,获得积分10
1分钟前
张利奥发布了新的文献求助10
1分钟前
奔跑应助hoanghl采纳,获得10
1分钟前
天天天晴完成签到 ,获得积分10
2分钟前
2分钟前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 2000
Bend stiffness of submarine cables – an experimental and numerical investigation 1000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7535979
求助须知:如何正确求助?哪些是违规求助? 9121123
关于积分的说明 19485313
捐赠科研通 7134728
什么是DOI,文献DOI怎么找? 3257429
关于科研通互助平台的介绍 2424711
邀请新用户注册赠送积分活动 2245276